Dataset Information

The Immune Signatures data resource, a compendium of systems vaccinology datasets.

ABSTRACT: Vaccines are among the most cost-effective public health interventions for preventing infection-induced morbidity and mortality, yet much remains to be learned regarding the mechanisms by which vaccines protect. Systems immunology combines traditional immunology with modern 'omic profiling techniques and computational modeling to promote rapid and transformative advances in vaccinology and vaccine discovery. The NIH/NIAID Human Immunology Project Consortium (HIPC) has leveraged systems immunology approaches to identify molecular signatures associated with the immunogenicity of many vaccines. However, comparative analyses have been limited by the distributed nature of some data, potential batch effects across studies, and the absence of multiple relevant studies from non-HIPC groups in ImmPort. To support comparative analyses across different vaccines, we have created the Immune Signatures Data Resource, a compendium of standardized systems vaccinology datasets. This data resource is available through ImmuneSpace, along with code to reproduce the processing and batch normalization starting from the underlying study data in ImmPort and the Gene Expression Omnibus (GEO). The current release comprises 1405 participants from 53 cohorts profiling the response to 24 different vaccines. This novel systems vaccinology data release represents a valuable resource for comparative and meta-analyses that will accelerate our understanding of mechanisms underlying vaccine responses.

SUBMITTER: Diray-Arce J

PROVIDER: S-EPMC9584267 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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The Immune Signatures data resource, a compendium of systems vaccinology datasets.

Diray-Arce Joann J Miller Helen E R HER Henrich Evan E Gerritsen Bram B Mulè Matthew P MP Fourati Slim S Gygi Jeremy J Hagan Thomas T Tomalin Lewis L Rychkov Dmitry D Kazmin Dmitri D Chawla Daniel G DG Meng Hailong H Dunn Patrick P Campbell John J Sarwal Minnie M Tsang John S JS Levy Ofer O Pulendran Bali B Sekaly Rafick R Floratos Aris A Gottardo Raphael R Kleinstein Steven H SH Suárez-Fariñas Mayte M

Scientific data 20221020 1

Vaccines are among the most cost-effective public health interventions for preventing infection-induced morbidity and mortality, yet much remains to be learned regarding the mechanisms by which vaccines protect. Systems immunology combines traditional immunology with modern 'omic profiling techniques and computational modeling to promote rapid and transformative advances in vaccinology and vaccine discovery. The NIH/NIAID Human Immunology Project Consortium (HIPC) has leveraged systems immunolog ...[more]

PMID: 36266291

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Project description:Background2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) is the most potent congener of the dioxin class of environmental contaminants. Exposure to TCDD causes a wide range of toxic outcomes, ranging from chloracne to acute lethality. The severity of toxicity is highly dependent on the aryl hydrocarbon receptor (AHR). Binding of TCDD to the AHR leads to changes in transcription of numerous genes. Studies evaluating the transcriptional changes brought on by TCDD may provide valuable insight into the role of the AHR in human health and disease. We therefore compiled a collection of transcriptomic datasets that can be used to aid the scientific community in better understanding the transcriptional effects of ligand-activated AHR.ResultsSpecifically, we have created a datasets package - TCDD.Transcriptomics - for the R statistical environment, consisting of 63 unique experiments comprising 377 samples, including various combinations of 3 species (human derived cell lines, mouse and rat), 4 tissue types (liver, kidney, white adipose tissue and hypothalamus) and a wide range of TCDD exposure times and doses. These datasets have been fully standardized using consistent preprocessing and annotation packages (available as of September 14, 2015). To demonstrate the utility of this R package, a subset of "AHR-core" genes were evaluated across the included datasets. Ahrr, Nqo1 and members of the Cyp family were significantly induced following exposure to TCDD across the studies as expected while Aldh3a1 was induced specifically in rat liver. Inmt was altered only in liver tissue and primarily by rat-AHR.ConclusionsAnalysis of the "AHR-core" genes demonstrates a continued need for studies surrounding the impact of AHR-activity on the transcriptome; genes believed to be consistently regulated by ligand-activated AHR show surprisingly little overlap across species and tissues. Until now, a comprehensive assessment of the transcriptome across these studies was challenging due to differences in array platforms, processing methods and annotation versions. We believe that this package, which is freely available for download ( http://labs.oicr.on.ca/boutros-lab/tcdd-transcriptomics ) will prove to be a highly beneficial resource to the scientific community evaluating the effects of TCDD exposure as well as the variety of functions of the AHR.

Dataset Information

The Immune Signatures data resource, a compendium of systems vaccinology datasets.

Publications

The Immune Signatures data resource, a compendium of systems vaccinology datasets.

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